Remember Parkinson’s Law? It states that the amount of work you have will expand to fill the available time. In this article, we’ll discuss the big data corollary to this law: The amount of data you collect will expand to consume your ability to store and process it. In other words, if it’s possible to collect more data, somebody will. That’s just what is happening in the application performance management (APM) space, or broadly speaking, IT operations management (ITOM) overall.
From log files to API-based telemetry, the quantity of data that such tools must now process is exploding. You might ask if such quantities of data qualify as big data. Just how big is big data anyway?
There is no official definition of big data, but a common one is data sets that are too large for traditional tools to store, process, or analyze. Big data, therefore, is a moving target. As tools mature, the threshold for big data continues to grow, continually pushing the boundaries of our ability to deal with increasingly large data sets.
Application performance management: Pushing into big data territory
APM has become a big data challenge, in part because in today’s digital world, applications never stand alone. Application performance depends on the performance of software infrastructure, the virtualization layer, the underlying hardware, and even the network itself. All of these supporting players generate increasingly massive quantities of data for the end application. Existing, first-generation APM tools simply aren’t up to this big data challenge. Managing today’s environments has become a big data problem, so it requires big data analytics techniques.
Read the entire article at http://techbeacon.com/apm-becoming-big-data-challenge-4-ways-deal-it.
